In machine vision-based industrial inspections, due to changes in conveyor speed or underexposure, the resulting image may produce motion blur, affecting the detection effect. In order to remove the motion blur, a fast linear motion blur method based on RL guided filter was proposed to evaluate the blur parameters of the image first, and the image blurring direction was evaluated using the spectral map integral of the image. Using auto-correlation method to obtain the blur kernel size; then through the proposed RL-guided filtering method to quickly remove the motion blur and suppress the ringing effect, to get a clear image, proved the accuracy of fuzzy kernel estimation Compared with TPKE and HQ, the proposed deblurring method is better for noise robustness and ringing suppression. Through the experiments of real-shot images under different speeds and different workpieces, the objective difference between the objective and the deblurred dimension measurements and the speed of operation were used to prove the superiority of this method in industrial inspection. The results show that the R_PSNR and R_SIMM is superior to the contrast method, which suppresses ringing while maintaining the sharpness of the edges. At the same time, the proposed method has a smaller influence on the measurement of the size and has an advantage over a small-sized workpiece. The maximum error is 0.31 pixels.